• DocumentCode
    2514965
  • Title

    Energy-saving scheduling strategy for elevator group control system based on ant colony optimization

  • Author

    Jing-long Zhang ; Jie Tang ; Qun Zong ; Jun-fang Li

  • Author_Institution
    Coll. of Electr. Eng. & Autom., Tianjin Univ., Tianjin, China
  • fYear
    2010
  • fDate
    28-30 Nov. 2010
  • Firstpage
    37
  • Lastpage
    40
  • Abstract
    Elevator group control scheduling is to dispatch every elevator to serve call requests from different floors based on some certain goal. It´s a kind of typical combinatorial optimization problems. Ant colony algorithm is good at solving the discrete combinatorial optimization, its well global optimization ability and quick convergence velocity are both necessary to a scheduling algorithm. Moreover, reducing passengers´ waiting and traveling time is the main focus of current dispatching algorithms, neglecting the energy consumed by the elevator system. So it´s necessary to research on energy-saving algorithms. For the purpose of elevator group´s energy-conservation run, the objective function of energy is built, ant colony model for elevator group control system is created, its optimization mechanism is figured out, and convergence of the algorithm is studied in this paper. Simulation results show the effectiveness of the strategy.
  • Keywords
    combinatorial mathematics; dispatching; energy conservation; lifts; optimisation; scheduling; ant colony optimization; convergence velocity; discrete combinatorial optimization; dispatching algorithm; elevator group control system; energy conservation; energy saving scheduling; scheduling algorithm; Ant colony optimization; Control systems; Convergence; Dispatching; Elevators; Floors; Optimization; ant colony optimization; dispatching algorithm; elevator group control system (EGCS); energy-saving;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Computing and Telecommunications (YC-ICT), 2010 IEEE Youth Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-8883-4
  • Type

    conf

  • DOI
    10.1109/YCICT.2010.5713146
  • Filename
    5713146